Real-Time and Accurate Drone Detection in a Video with a Static Background.

Ulzhalgas Seidaliyeva,Daryn Akhmetov,Lyazzat Ilipbayeva,Eric T Matson

doi:10.3390/s20143856

Abstract

With the increasing number of drones, the danger of their illegal use has become relevant. This has necessitated the creation of automatic drone protection systems. One of the important tasks solved by these systems is the reliable detection of drones near guarded objects. This problem can be solved using various methods. From the point of view of the price–quality ratio, the use of video cameras for a drone detection is of great interest. However, drone detection using visual information is hampered by the large similarity of drones to other objects, such as birds or airplanes. In addition, drones can reach very high speeds, so detection should be done in real time. This paper addresses the problem of real-time drone detection with high accuracy. We divided the drone detection task into two separate tasks: the detection of moving objects and the classification of the detected object into drone, bird, and background. The moving object detection is based on background subtraction, while classification is performed using a convolutional neural network (CNN). The experimental results showed that the proposed approach can achieve an accuracy comparable to existing approaches at high processing speed. We also concluded that the main limitation of our detector is the dependence of its performance on the presence of a moving background.

Highlights

With the constant development of technology, drone companies such as DJI, Parrot, and 3DRobotics are producing different types of unmanned aerial vehicles (UAVs) or systems (UAS)
True positives and false positives values were counted for an intersection over union (IoU) = 0.5
We present a real-time drone detection algorithm, the accuracy of which is comparable to existing algorithms

Summary

Introduction

With the constant development of technology, drone companies such as DJI, Parrot, and 3DRobotics are producing different types of unmanned aerial vehicles (UAVs) or systems (UAS). Because of their accessibility and ease of use, UAVs are widely used for commercial purposes, such as the delivery of goods and medicines, surveying, the monitoring of public places, cartography, search and rescue (SAR), first aid, and agriculture. Sequence such as background subtraction,in optical method,moving edge objects detection, andbasis frame. Optical flow is used for motion estimation in a video and detects moving objects objects’ relative velocities in the scene. By calculating the difference between flow method makes it inapplicable for real-time detection tasks. Despite its advantages, including quick to dynamic changes of extracts the moving objects

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Results

Discussion

Conclusion